Visualization Packages

Rendering HTML

import plotly
plotly.offline.init_notebook_mode()

Using Matplotlib

1. plot (x,y) - Plots a line from point(x axis) to point (y axis)

Sample Data Table

X	Y
0	4
10	4.68

Learn more on line plots

import matplotlib.pyplot as plt
import numpy as np
# make data
x = np.linspace(0, 10, 100)
y = 4 + 2 * np.sin(2 * x)

# plot
fig, ax = plt.subplots()

ax.plot(x, y, linewidth=2.0)

ax.set(xlim=(0, 8), xticks=np.arange(1, 8),
       ylim=(0, 8), yticks=np.arange(1, 8))

plt.show()

2. scatter(x,y) - Draws a scatter plot

X	Y
4.8	2.5

Learn more on scatter plot

plt.style.use('_mpl-gallery')

# make the data
np.random.seed(3)
x = 4 + np.random.normal(0, 2, 24)
y = 4 + np.random.normal(0, 2, len(x))
# size and color:
sizes = np.random.uniform(15, 80, len(x))
colors = np.random.uniform(15, 80, len(x))

# plot
fig, ax = plt.subplots()

ax.scatter(x, y, s=sizes, c=colors, vmin=0, vmax=100)

ax.set(xlim=(0, 8), xticks=np.arange(1, 8),
       ylim=(0, 8), yticks=np.arange(1, 8))

plt.show()

Using Seaborn

1. Seaborn.lmplot() method is used to plot data and draw regression model fits across grids where multiple plots can be plotted.

Leqrn more on Seaborn Implot

import seaborn as sns
sns.set_theme(style="ticks")

# Load the example dataset 
df = sns.load_dataset("anscombe")

sns.lmplot(
    data=df, x="x", y="y", col="dataset", hue="dataset",
    col_wrap=2, palette="muted", ci=None,
    height=4, scatter_kws={"s": 50, "alpha": 1}
)

<seaborn.axisgrid.FacetGrid at 0x21a6dffac10>

2. Seaborn.displot() - visualizing univariate and bivariate distribution of data

Learn more on Seaborn Displot

sns.set_theme(style="darkgrid")
df = sns.load_dataset("penguins")
sns.displot(
    df, x="flipper_length_mm", col="species", row="sex",
    binwidth=3, height=3, facet_kws=dict(margin_titles=True),
)

<seaborn.axisgrid.FacetGrid at 0x21a6eb57650>

Using Plotly

1. Bar chart with Plotly Express

Learn more on Plotly bar chart

import plotly.express as px
df = px.data.tips()
fig = px.bar(df, x="sex", y="total_bill", color="smoker", barmode="group")
fig.show()

2. Scatter Matrix with Plotly Express

Learn more on Scatter Matrix

df = px.data.iris()
fig = px.scatter_matrix(df, dimensions=["sepal_width", "sepal_length", "petal_width", "petal_length"], color="species")
fig.show()

Adding Image

from PIL import Image
img = Image.open('D:\AI & ML\ML FOUNDATION\LABS\CSCN-8010-labs\images\image1.png')
fig = plt.imshow(img)
plt.axis('off')
fig.axes.get_xaxis().set_visible(False)
fig.axes.get_yaxis().set_visible(False)